Attrition in Web-Based Treatment for Problem Drinkers

BackgroundWeb-based interventions for problem drinking are effective but characterized by high rates of attrition. There is a need to better understand attrition rates in order to improve the completion rates and the success of Web-based treatment programs. Object...

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Bibliographic Details
Main Authors: Postel, Marloes G, de Haan, Hein A, ter Huurne, Elke D, van der Palen, Job, Becker, Eni S, de Jong, Cor AJ
Format: Article
Language:English
Published: JMIR Publications 2011-12-01
Series:Journal of Medical Internet Research
Online Access:http://www.jmir.org/2011/4/e117/
Description
Summary:BackgroundWeb-based interventions for problem drinking are effective but characterized by high rates of attrition. There is a need to better understand attrition rates in order to improve the completion rates and the success of Web-based treatment programs. ObjectiveThe objectives of our study were to (1) examine attrition prevalence and pretreatment predictors of attrition in a sample of open-access users of a Web-based program for problem drinkers, and (2) to further explore attrition data from our randomized controlled trial (RCT) of the Web-based program. MethodsAttrition data from two groups of Dutch-speaking problem drinkers were collected: (1) open-access participants enrolled in the program in 2009 (n = 885), and (2) RCT participants (n = 156). Participants were classified as noncompleters if they did not complete all 12 treatment sessions (9 assignments and 3 assessments). In both samples we assessed prevalence of attrition and pretreatment predictors of treatment completion. Logistic regression analysis was used to explore predictors of treatment completion. In the RCT sample, we additionally measured reasons for noncompletion and participants’ suggestions to enhance treatment adherence. The qualitative data were analyzed using thematic analysis. ResultsThe open-access and RCT group differed significantly in the percentage of treatment completers (273/780, 35.0% vs 65/144, 45%, χ21 = 5.4, P = .02). Logistic regression analysis revealed a significant contribution of treatment readiness, gender, education level, age, baseline alcohol consumption, and readiness to change to predict treatment completion. The key reasons for noncompletion were personal reasons, dissatisfaction with the intervention, and satisfaction with their own improvement. The main suggestions for boosting strategies involved email notification and more flexibility in the intervention. ConclusionsThe challenge of Web-based alcohol treatment programs no longer seems to be their effectiveness but keeping participants involved until the end of the treatment program. Further research should investigate whether the suggested strategies to improve adherence decrease attrition rates in Web-based interventions. If we can succeed in improving attrition rates, the success of Web-based alcohol interventions will also improve and, as a consequence, their public health impact will increase. TrialInternational Standard Randomized Controlled Trial Number (ISRCTN): 39104853; http://www.controlled-trials.com/ISRCTN39104853 (Archived by WebCite at http://www.webcitation.org/63IKDul1T)
ISSN:1438-8871